Body scanning technologies have become increasingly popular in recent years. However, most proposed body scanners do not provide body skeleton information or body parts segmentation. This information is mostly extracted manually or requires a highly sophisticated body modeling framework to automatically compute. We invented an efficient skeleton estimation method in order to extract skeleton information and body parts automatically. Furthermore; our proposed approach can be performed reasonably fast on a cheap computing device.
Skeleton estimation provides useful information about the human body. This information enables wide fields of applications: Virtual clothes try-on for e-commerce, fitness tracking, medical application and/or game industry
From the CN 102622606 B a human skeleton extraction and orientation judging method based on a geodesic model is known. According to the geodesic model, five feature points located at four limbs and the tail end of the head top of the human body are automatically extracted and recognized, a geodesic distance of a vertex of the model is calculated by using the feature points as a start point, a center line of an equal geodesic distance curve group is extracted, the positions of the joint points are determined and skeletons are extracted on the center line according to relevant joint position information. The disadvantage of this method is that the position of the joint points is inexact.